14 citations · 15 across the 3 of their papers we have counts for
3 papers
Data Heterogeneity and Forgotten Labels in Split Federated Learning
Joana Tirana, Dimitra Tsigkari, David Solans Noguero +1
In Split Federated Learning (SFL), the clients collaboratively train a model with the help of a server by splitting the model into two parts. Part-1 is trained locally at each clie…
Workflow Optimization for Parallel Split Learning
Joana Tirana, Dimitra Tsigkari, George Iosifidis +1
Split learning (SL) has been recently proposed as a way to enable resource-constrained devices to train multi-parameter neural networks (NNs) and participate in federated learning…
MP-SL: Multihop Parallel Split Learning
Joana Tirana, Spyros Lalis, Dimitris Chatzopoulos
Federated Learning (FL) stands out as a widely adopted protocol facilitating the training of Machine Learning (ML) models while maintaining decentralized data. However, challenges…